AIMC Topic: Radiography, Panoramic

Clear Filters Showing 1 to 10 of 238 articles

Diagnostic competence of senior dental students in detecting caries on panoramic radiographs with and without artificial intelligence assistance: a cross-sectional studycaries detection on panoramic radiographs.

BMC medical education
PURPOSE: Accurate detection of proximal dental caries on panoramic radiographs is essential for effective treatment planning and preventive care. While senior dental students gradually develop interpretative competence during their training, artifici...

Multi-Regional deep learning models for identifying dental restorations and prosthesis in panoramic radiographs.

BMC oral health
BACKGROUND: This study introduces a novel deep learning methodology for the automated detection of a wide range of dental prostheses, including crowns, bridges, and implants, as well as various dental treatments such as fillings, root canal therapies...

End-to-end CNN-based detection of permanent first molars and prediction of root development stages from panoramic radiographs.

Scientific reports
The aim of this study was to develop a convolutional neural network (CNN)-based end-to-end learning architecture to predict the root development stages of permanent first molar teeth using panoramic radiographs. A dataset of 1629 first molar images w...

Hierarchical attention mechanism combined with deep neural networks for accurate semantic segmentation of dental structures in panoramic radiographs.

Scientific reports
Computer vision, a rapidly advancing branch of artificial intelligence (AI), has gained significant attention in medical and dental applications. Semantic segmentation, a key technique within computer vision, enables the precise identification and de...

Deep learning-based automated detection of supernumerary teeth in pediatric panoramic radiographs.

PloS one
INTRODUCTION: Supernumerary teeth are a common developmental anomaly in pediatric patients, potentially leading to complications such as impaction, crowding, and delayed eruption. Accurate and early detection is critical to prevent these sequelae and...

Distinguishing acute and chronic TMD in adolescent patients.

Scientific reports
This retrospective cross-sectional study aimed to elucidate the clinical and imaging characteristics of chronic temporomandibular disorder (TMD) compared to acute TMD in adolescents, and to identify factors associated with symptom chronicity. The stu...

Development and validation of artificial intelligence models for automated periodontitis staging and grading using panoramic radiographs.

BMC oral health
BACKGROUND: Periodontal diseases are common chronic conditions that can lead to tooth loss and systemic complications if not diagnosed and treated promptly. The 2017 classification by the American Academy of Periodontology highlights the need for eff...

Development and validation of an age estimation model based on dental characteristics using panoramic radiographs.

Scientific reports
Dental characteristics have considerable potential as indicators for estimating chronological age. This study developed a regression model for age estimation using dental characteristics observed in panoramic radiographs. A total of 2,391 radiographs...

Multi-label diagnosis of dental conditions from panoramic x-rays using attention-enhanced deep learning.

Oral and maxillofacial surgery
OBJECTIVE: This study aimed to develop and evaluate automated deep learning models for multi-class classification of dental conditions in panoramic X-ray images, comparing the effectiveness of custom CNN architectures with attention mechanisms, pre-t...

DenPAR: Annotated Intra-Oral Periapical Radiographs Dataset for Machine Learning.

Scientific data
Dental diseases are one of the most common diseases that affect humans. Clinicians employ several techniques for diagnosing and monitoring dental diseases, with intra-oral periapical (IOPA) radiographs being among the most commonly utilized methods. ...